I am a postdoctoral fellow in the lab of Arnold Kriegstein at the University of California, San Francisco (UCSF). I focus on applying single-cell genomics techniques to study the development of specific cell types of the human brain, as well as to understand how these cell types are affected in various diseases, especially autism. Before starting my work at UCSF, I did my PhD at the University of Miami focusing on genomic analysis of autism. I did my B.S. and MS at Moscow State University in my native Russia, where I worked on animal models of epilepsy and Alzheimer’s disease.
Dmitry Velmeshev
Postdoctoral Scholar
University of California, San Francisco
From this contributor
Single-cell analysis suggests brain signaling problems in autism
Recent advances in technology allow researchers to measure RNA that is contained within the nucleus of a single brain cell.

Single-cell analysis suggests brain signaling problems in autism
Explore more from The Transmitter
Cross-species connectome comparison shows uneven olfactory circuit evolution in flies
The findings start to reveal evolutionary changes that may have helped two species develop different olfactory preferences and adapt to their particular environments.

Cross-species connectome comparison shows uneven olfactory circuit evolution in flies
The findings start to reveal evolutionary changes that may have helped two species develop different olfactory preferences and adapt to their particular environments.
Null and Noteworthy: Downstream brain areas read visual cortex signals en masse in mice
The finding contradicts a theory that the regions prioritize neurons that are adept at identifying specific stimuli. Plus, a response to a study that questioned immune memory in astrocytes.

Null and Noteworthy: Downstream brain areas read visual cortex signals en masse in mice
The finding contradicts a theory that the regions prioritize neurons that are adept at identifying specific stimuli. Plus, a response to a study that questioned immune memory in astrocytes.
Poor image quality introduces systematic bias into large neuroimaging datasets
Analyses that include low-quality MRI data underestimate cortical thickness and overestimate cortical surface area, according to new findings from the Adolescent Brain Cognitive Development (ABCD) Study.

Poor image quality introduces systematic bias into large neuroimaging datasets
Analyses that include low-quality MRI data underestimate cortical thickness and overestimate cortical surface area, according to new findings from the Adolescent Brain Cognitive Development (ABCD) Study.